Method of and apparatus for processing image data for display by a multiple-view display device

ABSTRACT

A method is provided for processing image data for display by a multiple-view display device ( 24 ) so as to reduce the visibility of undesirable artefacts. Image pixel data are received ( 20, 21 ) representing the pixel brightnesses of respective images or sequences of images. The pixel data are processed ( 22 ) by applying a unidirectional filter. The processed pixel data for the images may then be interleaved ( 23 ) and supplied to the display device ( 24 ).

TECHNICAL FIELD

The present invention relates to a method of and an apparatus forprocessing image data for display by a multiple-view display device.

BACKGROUND ART

Multiple-view displays are known for providing autostereoscopic threedimensional image display and for displaying different images indifferent directions for different viewers. Examples of multiple-viewdisplays are disclosed in EP 0 829 744, GB 2 390 172 and EP 1 427 223.

WO 2006/043720 discloses a multiple-view display for use in a vehicle. Atechnique is disclosed for improving image quality so as to improve, forexample, brightness, contrast and scale of each image.

U.S. Pat. No. 6,973,210 and US 2005/0238228 disclose a technique formapping composite colour pixel groups to colour component pixels usinglowpass filters to achieve a desired degree of luminance and colouraccuracy. This technique requires a continuous three channel inputsignal or a discrete input which has a higher sampling frequency than isrequired by the output (or which has been scaled to have a highersampling frequency than the output). Sampling of the filtered result ishandled by selecting spatially different regions of the image data andmapping them to the colour component pixels rather than to the compositepixel groups.

US 2003/0210829 discloses a technique for enhancing image quality usinga combination of horizontally and vertically applied highpass andlowpass filters.

US 2006/0158466 discloses an image processing technique for displayingimages on a display having fewer pixels than in the original image. Thistechnique seeks to reduce the number of driving integrated circuitsrequired on the display.

Jinsung OH, Changhoon LEE and Younam KIM, “Minimum-Maximum ExclusiveWeighted-Mean Filter with Adaptive Window”, IEICE TRANS. FUNDAMENTALS,Vol. E88-A, No. 9, September 2005, pages 2451-2454 disclose an adaptivefilter for removing impulse noise from corrupted images. A conditionalfilter is applied depending on whether noise is detected. If noise isnot detected, the unprocessed pixel value is used. If noise is detected,the pixel value is replaced by a weighted sum of adjacent pixel valuesnot affected by noise.

WO06110646A2 discloses an autostereoscopic display using a slantedlenticular component and a method of improving image quality by applying“bleed-through” and blurring. “Bleed-through” occurs when data for apixel for a given view is also visible in a neighbouring view. This maybe because the arrangement of the lenticular component is such that apixel is physically visible in both views or, by processing the image,data from one view is overlaid on a neighbouring view, for example by ablurring operation. Furthermore the blur function used in WO06110646A2is a standard function such as that found in Photoshop image processingsoftware.

Many known multiple-view displays are based on a display device in theform of a spatial light modulator, such as a liquid crystal device,whose pixel structure cooperates with a parallax optic, such as aparallel barrier or a lenticular screen, to control the viewing regionsfrom which the pixels are visible. A typical example of such anarrangement is shown in FIG. 1 of the accompanying drawings. Theindividual colour component pixels (sub-pixel components) receiveinterlaced image data from two images to provide a two-view display. Thered, green and blue pixels are indicated by R, G and B, respectively.The pixels displaying the first and second images are identified by thesubscripts 1 and 2. The pixel structure is aligned with slits in aparallax barrier 1 so that only those pixels R₁, G₁ and B₁ displayingthe first image are visible to viewer 1 whereas only those pixels R₂, G₂and B₂ displaying the second image are visible to viewer 2.

Some undesirable colour artefacts may become visible for certain imagefeatures and an example of this is illustrated in FIG. 1. In thisexample, both views contain an image feature which is one compositecolour pixel group wide as illustrated at 2. The adjacent compositecolour pixel groups are black as shown, for example, at 3 and 4. Thedisplayed feature is intended to be white. However, viewer 1 sees onlythe green component pixel G1 of this feature whereas the viewer 2 seesonly the red and blue components of this feature. Thus, a feature whichshould appear to be white is perceived as being either green or magenta.Thus, for features such as narrow lines or “sharp” edges, incorrectcolours may be perceived.

FIG. 2 of the accompanying drawings illustrates by way of example twotypes of parallax barrier displays. The type shown in the upper part ofFIG. 2 at (a) is of the strip barrier type in which elongate slitsextending throughout the height of the barrier are separated by opaqueregions. The display shown at (b) in FIG. 2 has a different type ofparallax barrier, in which the “slits” or apertures are arranged in acheckerboard pattern. The undesirable colour artefacts describedhereinbefore can occur with either type of barrier, and with otherbarrier types and other types of parallax optics.

DISCLOSURE OF INVENTION

According to a first aspect of the invention, there is provided a methodof processing image data for display by a multiple-view display device,comprising: receiving a plurality of sets of image pixel data, whereeach set represents the pixel brightness of a respective image orsequence of images; and processing the sets of pixel data by applying aunidirectional filter to each of at least one of the sets.

All of the sets may be processed by respective unidirectional filtersbefore interleaving. The unidirectional filters may be of the same type.

Each set may comprise composite colour component pixel group data andthe or each filter may operate on adjacent composite pixel groups. Theor each filter may operate on the pixel data of the same colourcomponents of the adjacent composite pixel groups.

The or each filter may form each processed pixel data as a linearcombination of the unprocessed pixel data and at least one adjacentpixel data. The at least one adjacent pixel data may be one adjacentpixel data. The linear combination may be a normalised linearcombination. The at least one adjacent pixel data may represent at leastone horizontally adjacent pixel.

The or each filter may operate in real time.

According to a second aspect of the invention, there is provided amethod of processing image data for display by a multiple-view displaydevice, comprising: receiving a plurality of sets of image pixel data,where each set represents the pixel brightnesses of a respective imageor sequence of images; processing the sets of pixel data by comparing,for each of a plurality of subsets of each of at least one of the setswhere each subset represents the brightnesses of a same number of pixelgroups and each pixel group comprises at least one pixel, the brightnesspattern of the pixel groups of the subset with a first predeterminedpattern; and, if the pixel brightness pattern substantially matches thefirst predetermined pattern, applying a first filter to derive a firstprocessed brightness of at least one of the pixel groups of the subset.

The comparing step may comprise forming the difference between thebrightnesses of immediately adjacent pixel groups of each subset. Thecomparing step may further comprise comparing the differences with atleast one threshold.

Each pixel group may comprise a composite colour pixel group of colourcomponent pixels. The brightness of each pixel group may be formed as aweighted sum of the brightnesses of the colour component pixels. As analternative, the brightness of each pixel group may be formed as thebrightness of one of the colour component pixels. The brightness of eachpixel group may be formed as the brightness of a green one of the colourcomponent pixels.

If the pixel brightness pattern does not substantially match the firstpredetermined pattern, a second filter may be applied to derive a secondprocessed brightness of the at least one of the pixel groups. The secondfilter may be a unidirectional filter.

If the pixel brightness pattern does not substantially match the firstpredetermined pattern, no filter may be applied for deriving thebrightness of the at least one of the pixel groups.

The method may comprise, for each of the plurality of subsets, comparingthe brightness pattern of the pixel groups of the subset with a secondpredetermined pattern and, if the pixel brightness pattern substantiallymatches the second predetermined pattern, applying a third filter toderive a third processed brightness of at least one of the pixel groupsof the subset.

The pixels of each subset may be contiguous and may extend substantiallyin one dimension.

The pixels of each subset may comprise a contiguous two dimensionalarrangement.

The comparing step may be repeated following receipt of each pixel groupdata.

The method may comprise interleaving the processed sets for supply tothe display device.

According to a third aspect of the invention, there is provided a methodof processing image data for display by a multiple-view display device,comprising: receiving a plurality of sets of image pixel data, whereeach set represents the pixel brightnesses of a respective image orsequence of images; and processing the sets of pixel data by applying,to each pixel of each of at least one of the sets, a correction tocompensate for the absence of at least one omitted adjacent pixel of thesame set.

The at least one omitted adjacent pixel may be omitted during asubsequent interleaving step.

The method may comprise performing the interleaving step on theprocessed sets for supply to the display device.

The at least one of the sets may comprise all of the sets.

The pixels may represent grey levels of monochrome images.

The pixels may represent brightnesses of colour components and at leastone omitted adjacent pixel may be of the same colour component as thepixel.

The correction may comprise replacing the pixel data with datarepresenting a linear combination of the pixel data and at least oneadjacent pixel data. The linear combination may comprise a normaliseddifference between: a normalised weighted sum of the pixel data and aplurality of the adjacent pixel data; and a weighted sum of the adjacentpixel data omitting the omitted adjacent pixel data. The weights of thenormalised sum may be substantially in accordance with at least oneGaussian function. The at least one function may comprise a functionwhich is rotationally symmetrical about the pixel being processed. As analternative, the at least one function may comprise a first horizontalGaussian function having a first standard derivation and a secondvertical Gaussian function having a second standard deviation differentfrom the first standard deviation. The first standard deviation may beless than the second standard deviation. The weights may be integerapproximations to the or each Gaussian function.

The display device may be arranged to display the images or imagesequences simultaneously.

The display device may be and interleaved image display device.

The display device may comprise an image display device and a parallaxoptic.

The sets may comprise respective serial data streams.

According to a fourth aspect of the invention, there is provided anapparatus arranged to perform a method according to the first or secondor third aspect of the invention.

It is thus possible to provide techniques which allow the undesirablecolour artefacts described hereinbefore to be removed or made lessperceptible to a viewer. Image sharpness in the displayed images can beimproved as compared with known image filtering techniques. Lessprocessing resources are required than with the more complex knowntechniques of processing images. For example, processing may beperformed in an application specific integrated circuit (ASIC) or in afield programmable gate array (FPGA) and less “resource” is required.For example, the processing may be performed with any one or more of:fewer gates; less memory for buffering data; less stringent timing;lower latency; and lower power consumption.

In embodiments where the actual filtering applied to the image dependson detection of one or more image features, improved perceived imagequality may be obtained. For example, instead of applying a generalpurpose filter irrespective of the image content, the filtering may beselected according to features of image content. Perceived colour faultsand image sharpness may thus be improved.

It is also possible to compensate at least partially for the visualeffects of the loss of pixels which are omitted during an interleavingprocess.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a schematic cross-sectional diagram illustrating a known typeof multiple-view display;

FIG. 2 is a diagrammatic view illustrating different types of parallaxbarriers;

FIG. 3 is a block schematic diagram illustrating a vehicle displayarrangement;

FIG. 4 is a block schematic diagram illustrating part of the arrangementof FIG. 3 in more detail;

FIG. 5 illustrates at (a) and (b) different interleaving techniques forinterleaving two images;

FIG. 6 is a block schematic diagram illustrating data flow through imageprocessing in the arrangement shown in FIG. 3;

FIG. 7 is a diagram illustrating horizontal filtering of an imageconstituting an embodiment of the invention;

FIG. 8 is a diagram illustrating different types of filters;

FIG. 9 is a diagram illustrating further filter types;

FIG. 10 is a diagram illustrating the determining of a greyscale profilefor a 4×1 window;

FIG. 11 is a flow diagram illustrating a conditional pixel processingtechnique constituting an embodiment of the invention;

FIG. 12 is a flow diagram illustrating another conditional pixelprocessing technique constituting an embodiment of the invention;

FIG. 13 is a flow diagram illustrating a further conditional pixelprocessing technique constituting an embodiment of the invention;

FIG. 14 is a flow diagram illustrating yet another conditional pixelprocessing technique constituting an embodiment of the invention;

FIG. 15 is a flow diagram illustrating yet a further conditional pixelprocessing technique constituting an embodiment of the invention;

FIG. 16 is a diagram illustrating processing using a 3×3 window;

FIG. 17 illustrates window profiles for various image features;

FIG. 18 illustrates the use of a 3×3 filter; and

FIG. 19 illustrates examples of filter weights.

BEST MODE FOR CARRYING OUT THE INVENTION

The arrangement shown in FIG. 3 comprises a multiple-view (multiview)display 10, which is mounted in the dashboard of a vehicle and providesindependently selectable images or image sequences to be viewed by avehicle driver and a front-seat passenger. The system includes an in-carentertainment system 11 which, for example, includes a DVD player forsupplying entertainment images. Such images must be visible only to apassenger when the vehicle is in use but may be made available to thedriver when the vehicle is not in use. The system further comprises asatellite navigation system 12 for supplying navigation images. Suchimages are generally required to be visible to the driver when thevehicle is in use and may be viewed by the passenger whenever thepassenger wishes to view them.

The image data from the in-car entertainment system 11 and from thesatellite navigation system 12 are supplied to an image processing unit13, which performs filtering processes as described hereinafter. Theunit 13 also interleaves (interlaces) the data for the two images to beviewed simultaneously by the different viewers so as to complete theimage processing prior to display. The processed data are then suppliedto driver electronics 14, which in turn supply the appropriate signalsto the display device, such as a liquid crystal device, within themultiple-view display device 10. The display device 10 also includes aparallax barrier which, in this embodiment, has a chequerboard patternof slits or apertures. However, any suitable slit pattern may be used,such as continuous vertical slits, and other parallax optics may beused, such as lenticular screens.

FIG. 4 illustrates schematically the basic processing steps performedwithin the image processing unit 13. Processing for x images forsimultaneously viewing by x viewers is illustrated. The input data foreach image is individually processed in respective process steps 15 ₁,15 ₂, . . . , 15 _(x) as described in more detail hereinafter. The datafor the individually processed images are then supplied to a dataformatting step 16 which formats the data into the required format fordisplay by the display device. In particular, the step 16 performs theinterleaving or interlacing so that the individual images are displayedas interleaved colour component pixels in the display device.

FIG. 5 illustrates two examples of interleaving the image data for twoimages, although any suitable type of interleaving may be used. In theexample illustrated at (a), each of the images “view 1” and “view 2” isprocessed in the steps 15 ₁ and 15 ₂ such that alternate colourcomponent pixels in each image are ignored. Thus, each image isdisplayed with half of its original horizontal spatial resolution.

In the interleaving technique shown at (b) in FIG. 5, the images areprocessed so as to reduce the horizontal resolution to half that of theoriginal image. The resulting data for the images are then combined inthe correct order for display by the display device.

The number of inputs may vary. A lower input is where all of the viewerssee the same image simultaneously. Conversely, an upper limit isdetermined by the maximum number of images or views which the displaydevice can display simultaneously. Processing of the images beforeinterleaving the image data permits the best image sharpness to beprovided while reducing or eliminating undesirable visible artefactssuch as undesirable colour artefacts.

FIG. 6 illustrates the flow of data through the image processing. Theimage data for each view are supplied at 20, typically in serial dataword format with each word representing the image data for a compositecolour pixel group. Buffering is then provided at 21 for N compositecolour pixels, each of which comprise red, green and blue colourcomponent data. The number N of pixels which are required in thebuffering must be sufficient to permit the subsequent processing to beperformed. In order to permit the simplest filtering as describedhereinafter, it is sufficient to buffer one pixel but other examples offiltering described hereinafter require sufficient buffering for morethan one composite colour pixel group. The current and bufferedcomposite colour pixel groups are then processed at 22 so as to provideprocessed data for one of the composite colour pixel groups and theprocessed pixel data are output at 23. The data are then displayed at24, for example by refreshing the display device in accordance with itsrequirements.

In a set of embodiments of the invention, the pixel processing step 22comprises applying filtering to the incoming image pixel data and FIG. 7illustrates the type of filtering which is applied. In theseembodiments, the same filter is applied to all of the pixels and is ofthe unidirectional type. Thus, the processed value for each pixel is afunction, such as a linear combination, of the incoming values for thepixel being processed and one or more adjacent pixels forming a straightline on one side of the pixel being processed. FIG. 7 illustrates aslightly more general type of “one dimensional horizontal” filter whichis such that the filter is applied to each pixel p_(n−1) when the pixelp_(n) has been received.

If the values of the horizontally adjacent pixels are represented byp_(n−2), p_(n−1) and p_(n), then the processed value of the pixelp_(n−1) is given by

f(p _(n−1))=(1/S)((A.p _(n−2))+(B.p _(n−1))+(C.p _(n)))

where A, B and C are the filter coefficients and are generally constantsand S performs normalising of the processed pixel value and is generallyequal to (A+B+C).

Where the pixels values pi relate to single monochrome or black andwhite pixels, the pixel values for the three adjacent pixels areprocessed. However, in the case of composite colour pixel groups, eachof which comprises red, green and blue pixels, the filter is applied inturn to each of the colour component pixel values of the adjacentcomposite pixel groups.

FIG. 7 gives an example of a unidirectional filter whose coefficients A,B and C have the values 0, 1 and 1, so that S is equal to two. Thefilter is applied to pixel values 1, 0.5, and 0 so that the processedvalue of the pixel p_(n−1) is 0.25.

The same filter may be used for each of the colour components of theadjacent composite colour pixel groups but this is not essential anddifferent filters may be applied to different colour component pixels.The example of the filter shown in FIG. 7 is unidirectional because the“leading” coefficient A is set to zero so that the processed pixel datafor the pixel p_(n−1) is a function of that pixel and the pixel to theright of it. Other examples of filters are given in FIG. 8. The filtersshown at 25, 26 and 27 are unidirectional filters whereas the filterillustrated at 28 is not unidirectional as the value of each processedpixel is derived from the unprocessed values of that pixel and thehorizontally immediately adjacent pixels on both sides.

It has been found that, for many applications, a relatively simpleunidirectional filter may be applied to the image data and achieves asubstantial improvement in removing or reducing the visibility of colourartefacts of the type described hereinbefore. Further, such a filterprovides relatively little image blurring so that the processed imagesremain relatively sharp. Such a filter requires relatively little pixelbuffering and processing resources and may therefore be implementedeasily and with minimal penalty in terms of complexity and cost.

In another set of embodiments of the invention, improved performance isachieved by identifying one or more features in the images to beprocessed and applying different filtering according to the identifiedfeatures. Image features may be identified by measuring the greyscaledifferences between neighbouring pixels forming a window around thecurrent pixel and one or more neighbouring pixels. For example, in thesimplest case, the window may be two pixels wide and one pixel high toprovide a 2×1 window. The difference in greyscale between the pixels inthe window is calculated and compared with one or more thresholds todetermine whether the greyscale difference is “high” or “low”. A singlethreshold may be used and the difference may be categorised as high orlow depending on whether the greyscale difference is above or below thethreshold. Alternatively, different thresholds may be used so that thegreyscale difference has to exceed a first threshold to be categorisedas high and has to be less than a second threshold, below the firstthreshold, to be categorised low. The categorisation may then be used todetermine whether filtering is applied to the current pixel, or which oftwo possible filters is applied. For example, when the difference iscategorised as high, a unidirectional filter of the type describedhereinbefore may be applied whereas, when the difference is categorisedas low, no filter is applied. Such a technique allows filtering to beapplied to one side of certain edges or lines such that filtering isonly applied when necessary or desirable. In this context and throughoutthe specification, the term “difference” refers to the absolute value or“magnitude” of the difference.

There are image features which may be processed incorrectly by applyinga filter simply based on the greyscale change between neighbouringpixels. An example of such a feature is a line which is two pixels wide.Such a line will suffer from colour artefacts if a unidirectional filteris applied to it. By detecting a feature of this type, a special filtermay be applied in place of, for example, a unidirectional filter whichis applied elsewhere.

Another example of an image feature which should be detected is a linewhich is a single pixel wide.

By using a 4×1 window, features such as two pixel wide lines can bedetected with good reliability so that the appropriate “conditionalfiltering” may be applied. As illustrated in FIG. 10, four horizontallyadjacent pixels including the pixel p_(n−1) currently being processedare assessed by performing a subtraction of pixel values for immediatelyadjacent pairs of pixels and then performing the comparison as describedhereinbefore to determine a high (H) or low (L) greyscale difference.Thus, an intensity profile may be determined as a sequence where eachelement comprises H or L. A two pixel wide line will then be indicatedby the intensity profile HLH.

FIG. 9 gives some examples of “special case” filters which may be used,including the filtering coefficients shown at 30 for no filtering. Bytesting for intensity profile patterns corresponding to specificfeatures, choices may be made about whether to apply a filter to thecurrent pixel and, if so, which of a plurality of available filtersshould be applied.

FIG. 11 illustrates an example of conditional processing for the currentpixel p_(n) based on a 4×1 window. When the next pixel p_(n+1) isreceived, the difference profile is determined in a step 31 and a step32 determines whether this matches the HLH pattern indicative of a twopixel wide line. If not, then a step 33 applies a unidirectional filterto the current pixel and the processed pixel value, or set of values, isoutput at 34. Conversely, if a match is found, then a special casefilter is applied and the resulting processed data are output by thesteps 35 and 34. In this particular example, once a two pixel wide linehas been identified, the unidirectional filter has already been appliedto the left hand edge, so that a special case filter is applied to theright hand edge of the line. It is thus possible to avoid adding orcreating an undesirable colour artefact to the perceived image.

The conditional processing illustrated in FIG. 12 is similar to thatillustrated in FIG. 11, except that a special case filter is applied tothe left hand edge of a two pixel wide line. The unidirectional filteris then applied to the right hand edge of the line.

FIG. 13 illustrates conditional processing such that a special casefilter is applied to the pixel after the right hand edge of the feature.The grey scale profile is determined in the step 31 and a step 36determines whether a special flag is raised. If not, the step 32determines whether the grey scale profile matches the HLH pattern. Ifnot, the unidirectional filter is applied to the pixel p_(n−1) in thestep 33. Otherwise, no filter is applied to the pixel p_(n) in a step 37but a special flag is raised in a step 38.

When the step 36 determines that the special flag is raised, a specialcase filter is applied to the pixel p_(n) in a step 39. The special flagis then cleared in a step 40. Thus, when a two pixel wide line isidentified, a unidirectional filter is applied to the left hand edge, nofilter is applied to the line itself, and a special case filter isapplied to the pixel after the right hand edge.

FIG. 14 illustrates conditional processing such that no processing takesplace around the identified feature. The current pixel to be processedis at the left hand end of the 4×1 window.

After determining the greyscale profile, a step 41 determines whether acounter value I is equal to zero. If not, the step 43 applies no filterto the current pixel and a step 44 decrements the counter value by one.When the step 41 determines that the counter value I is equal to zero,the step 32 determines whether the greyscale profile matches the HLHpattern representing a two bit wide line. If so, a step 37 applies nofilter and a step 42 sets the counter value I equal to 2. If there is nomatch in the step 32, a unidirectional filter is applied in the step 33.

Thus, when the HLH pattern is detected in the grey scale profile, nofilter is applied but the counter is set to 2. As the next two pixelsare processed, the counter has a non-zero value so that no filter isapplied to either of these pixels. When the next pixel arrives, thecounter has returned to zero so that a unidirectional filter is appliedas normal.

The conditional processing illustrated in FIG. 15 differs from thatillustrated in FIG. 14 in that special case filters are applied to bothsides of the two pixel wide line. Thus, the steps 41, 32, 33, 27 and 42are substantially the same as the corresponding steps in FIG. 14 expectthat the step 37 applies a first special filter A to the pixel p_(n).

When the step 41 determines that the counter value I is not equal tozero, a step 46 determines whether I is equal to 2. If not, then anotherspecial filter B is applied to the pixel p_(n) in the step 48. If I isequal to 2, then no filter is applied by the step 47. In either case,the step 44 decrements the counter value by 1. Thus the special filter Ais applied to the left hand edge of the two pixel wide line, the specialfilter B is applied to the right hand edge of the line, no filtering isapplied to the line itself and a unidirectional filter is appliedelsewhere.

Other window sizes may be applied around the current pixel, for exampleso as to detect other image features which may require differentprocessing. Test windows may extend vertically as well as or instead ofhorizontally and examples of window sizes which may be used are 2×1,1×2, 2×2 and 3×3.

An example of a “square” window which is 3 pixels wide and 3 pixels highis illustrated in FIG. 16 with the current pixel being disposed at thecentre position of the window.

The greyscale difference profile in this example is evaluated bycomparing the grey level difference between the current pixel and eachof the surrounding pixels. A specific example of such a profile forexemplary pixel values is illustrated in FIG. 16. The resulting profileis then compared against a set of profiles to determine the presence ofa particular image feature and an example of a set of such profiles isillustrated in FIG. 17. The values H and L are as described hereinbeforebut a value I is assigned to any pixel where its value is irrelevant tothe test for the image feature. Thus, the patterns shown at (a) and (b)allow diagonal lines to be identified, the patterns shown at (c) and (d)allow end points of horizontal lines to be identified and the patternsshown at (e) and (f) allow end points of vertical lines to beidentified.

As before, a filter may be applied to the pixels in the window byapplying weights to each pixel, summing the results and normalising.This is illustrated in the upper part of FIG. 18 and a specific exampleis illustrated in the lower part for actual values of the filterparameters and the pixels in the window. A different filter may beassociated with each test pattern so as to provide improved quality ofimage processing. Specific examples of such filters are illustrated inFIG. 19. Thus, the filter f in FIG. 19 may be applied if the profilematches the test pattern shown at f) in FIG. 17, the filter e may beapplied for the test pattern e), the filter c may be applied for thetest pattern c), and the bottom left filter in FIG. 19 may be appliedfor the remaining test patterns a), b) and d).

In order to make use of these test patterns, it is necessary to buffer alarger number of pixels so that all of the window pixels are availablefor each current pixel being processed. Thus, in the case of the 3×3window, just over two rows of pixel data are required to be buffered inorder for the processing to be performed.

It is possible to reduce the number of calculations which have to beperformed for processing each pixel by storing some results fromprevious pixel processing. For example, the greyscale difference betweenpixels of each pair is constant for the current image so that the H or Lvalues for previous pixel pairs may be stored for subsequent use. In theexample of the 4×1 window, the most recent two results may be stored sothat only one pixel difference calculation is required when processingeach new pixel. In the case of the 3×3 window, four results may bestored for each pixel. Four new results then have to be calculated foreach new pixel to be processed instead of calculating eight results.Thus, by storing previous results, there is an increase in memoryrequirements but a decrease in processing requirements.

As mentioned hereinbefore, different threshold values may be used todetermine the H and L values of greyscale differences. For example, thehigh threshold may be 0.3 whereas the low threshold may be 0.1 for acomparison range from 0 to 1.

The greyscale difference threshold testing described hereinbefore may beperformed in various ways for colour displays where each compositecolour pixel group comprises different colour component pixels such asred, green and blue. In one example, the red, green and blue data areconverted to a single greyscale value using standard weighting beforeperforming the comparisons between full-colour pixel groups. In anotherexample, the red, green and blue values are separately compared withthresholds weighted by an amounted related to the weighting used forred, green or blue when converted to greyscale. In a further example,the red, green and blue data may be converted to single greyscale valuesusing weightings suitable for hardware implementation, for exampleemploying multiplication or division by powers of 2, after which theresulting greyscales are compared. In yet another example, a singlecolour component may be used to represent the full-colour pixel groupgrey level. For example, the green colour component may be used torepresent the grey level as green is generally the dominant colourcomponent and makes the largest contribution to the greyscale equivalentof a full-colour pixel group.

Another undesirable visual artefact occurs in some types ofmultiple-view displays because of the interleaving process. Inparticular, the perceived brightness of each pixel is influenced by thebrightnesses of adjacent pixels.

When the pixel data for the different images or sequences of images areinterleaved for display on the display device, each pixel is surroundedby fewer visible sub-pixels than in the original image before processingand interleaving. In the absence of any correction for this effect, thepixel appears different to a human observer than is intended. In orderto overcome or reduce this effect, a correction is applied to each pixelas follows.

The appearance of a pixel is influenced by the appearance of theadjacent or surrounding pixels in the original image and the pixelappearance as perceived by a human observer is determined by summing theweighted contributions of the pixel and its neighbours. In the casewhere the display provides monochrome or black-and-white images, all ofthe pixels within a window contribute to the weighted sum. In the caseof a full-colour display or the like comprising colour composite pixelgroups of different colour component pixels, only those sub-pixels ofthe same colour are considered within the window.

In a typical example, a window comprising three rows and three columnsof pixels is centred on the pixel being processed. For example, eachcolour component of a composite colour pixel group may be processed inturn and, for the red colour component pixel V_(xy), the eightimmediately adjacent red component pixels are within the window. Theactual appearance or brightness V_(r) of the pixel V_(xy) is obtained bya linear combination of the contributions of the pixels within thewindow in the form of a weighted sum as follows:

$V_{r} = {\sum\; \begin{Bmatrix}{w_{1}*V_{{x - 1},{y - 1}}} & {w_{2\; a}*V_{x,{y - 1}}} & {w_{1}*V_{{x + 1},{y - 1}}} \\{w_{2\; b}*V_{{x - 1},y}} & {w_{3}*V_{x,y}} & {w_{2\; b}*V_{{x + 1},y}} \\{w_{1}*V_{{x - 1},{y + 1}}} & {w_{2\; a}*V_{x,{y + 1}}} & {w_{1}*V_{{x + 1},{y + 1}}}\end{Bmatrix}}$

where the contribution of the pixel being processed is weighted by aweight w3, the contributions of the vertically adjacent pixels V_(x,y−1)and V_(x,y+1) are weighted with a weight w_(2a), the contributions ofthe horizontally adjacent pixels V_(x−1,y) and V_(x+1,y) are weightedwith a weight w_(2b), the diagonally adjacent pixels V_(x−1,y−1),V_(x+1,y−1), V_(x−1,y+1) and V_(x+1,y+1) are weighted with a weight w₁,the contributions within the brackets are summed to form the linearcombination or weighted sum, and the relative positions of the pixel inthe image are as illustrated within the brackets.

After the image interleaving process to form a spatially multiplexedcomposite image on the display device, several of the pixels are omittedfrom the window in a pattern corresponding to, for example, the patternof parallax elements such as apertures in a parallax optic such as aparallax barrier. For example, in the case where a checker barrier ofthe type shown at (b) in FIG. 2 is used, the horizontally and verticallyadjacent pixels are omitted in the interleaving process and therefore donot contribute to the appearance of the pixel V_(x,y) when themultiple-view display is viewed by a human observer. Instead, theappearance V_(p) of the pixel V_(x,y) to someone observing the pixel onthe multiple-view display device is given by:

$V_{p} = {W*{\sum\; \begin{Bmatrix}{w_{1}*V_{{x - 1},{y - 1}}} & \; & {w_{1}*V_{{x + 1},{y - 1}}} \\\; & {w_{3}*V_{x,y}} & \; \\{w_{1}*V_{{x - 1},{y + 1}}} & \; & {w_{1}*V_{{x + 1},{y + 1}}}\end{Bmatrix}}}$

where W=(4w₁+2*w_(2a)+2*w_(2b)+w₃)/(4*w₁+w₃)

In order for the pixel to appear as intended, its data or value iscorrected to a new value V′_(x,y) so as to give the perceived appearanceV_(r). The corrected value is then found from the following equation:

${\sum\; \begin{Bmatrix}{w_{1}*V_{{x - 1},{y - 1}}} & {w_{2\; a}*V_{x,{y - 1}}} & {w_{1}*V_{{x + 1},{y - 1}}} \\{w_{2\; b}*V_{{x - 1},y}} & {w_{3}*V_{x,y}} & {w_{2\; b}*V_{{x + 1},y}} \\{w_{1}*V_{{x - 1},{y + 1}}} & {w_{2\; a}*V_{x,{y - 1}}} & {w_{1}*V_{{x + 1},{y + 1}}}\end{Bmatrix}} = {W*{\sum\; \begin{Bmatrix}{w_{1}*V_{{x - 1},{y - 1}}} & \; & {w_{1}*V_{{x + 1},{y - 1}}} \\\; & {w_{3}*V_{x,y}^{\prime}} & \; \\{w_{1}*V_{{x - 1},{y + 1}}} & \; & {w_{1}*V_{{x + 1},{y + 1}}}\end{Bmatrix}}}$

This equation is solved for V′_(x,y) to give:

$V_{x,y}^{\prime} = {\frac{1}{w\; 3}\begin{Bmatrix}{{\frac{1}{W}{\sum\; \begin{Bmatrix}{w_{1}*V_{{x - 1},{y - 1}}} & {w_{2\; a}*V_{x,{y - 1}}} & {w_{1}*V_{{x + 1},{y - 1}}} \\{w_{2\; b}*V_{{x - 1},y}} & {w_{3}*V_{x,y}} & {w_{2\; b}*V_{{x + 1},y}} \\{w_{1}*V_{{x - 1},{y + 1}}} & {w_{2\; a}*V_{x,{y + 1}}} & {w_{1}*V_{{x + 1},{y + 1}}}\end{Bmatrix}}} -} \\{\sum\begin{Bmatrix}{w_{1}*V_{{x - 1},{y - 1}}} & \; & {w_{1}*V_{{x + 1},{y - 1}}} \\\; & \; & \; \\{w_{1}*V_{{x - 1},{y + 1}}} & \; & {w_{1}*V_{{x + 1},{y + 1}}}\end{Bmatrix}}\end{Bmatrix}}$

so as to give the corrected brightness or grey level for the pixel beingprocessed. By applying this to each pixel of the original images beforeinterleaving (with or without the further processing describedhereinbefore), it is possible to compensate for the pixels which areomitted by the interleaving process. Although these pixels are replacedby pixels corresponding to another image or sequence, such other pixelsare obscured by the parallax optic and do not, therefore, contribute tothe appearance of the pixel being processed.

The weights w₁, w_(2a), w_(2b) and w₃ are chosen so as to provide theappropriate correction or compensation for the “missing” pixels. In atypical example, the weights are chosen according to a Gaussian functionof distance on the display device from the pixel being processed. Forexample, the weights may have the following values:

w₁=0.0240, w_(2a)=w_(2b)=0.1070, w₃=0.4759

These weights are appropriate for a rotationally symmetrical Gaussianfunction centred on the pixel being processed for equal vertical andhorizontal spacing of the pixels on the display device.

Although these weights have been found to provide good quality results,the processing requires multiplication operations and is relativelyexpensive in terms of hardware. Acceptable results may be achieved bychoosing integer values of the weights so as to approximate the Gaussianfunction, requiring only shift, add and subtract operations to beperformed. An example of suitable integer weights is as follows:

w₁=1, w_(2a)=w_(2b)=2, w₃=4

In another example of integer approximations to Gaussian functions,vertical and horizontal Gaussian functions of different standarddeviations may be used. An example of suitable integer value weightingsis as follows:

w₁=1, w_(2a)=8, w_(2b)=2, w₃=16

In this case, the standard deviation of the horizontal Gaussian functionis less than that of the vertical Gaussian function. This allows adifferent compromise between smoothing and correction of the visualartefact to be provided in the two orthogonal axes. This smoothing andcorrection takes advantage of the tendency of the human eye to be moresensitive to resolution in the horizontal direction than in the verticaldirection.

The above processing may be performed for every pixel irrespective ofthe values of V_(p) and V_(r). Alternatively, processing may depend onthe values of V_(p) and V_(r). For example, if the absolute value|V_(r)-V_(p)| of the difference between V_(p) and V_(r) is greater thana predetermined threshold, the processed value may be used whereas,otherwise, the unprocessed value may be used.

The techniques described hereinbefore may be implemented in softwareused to control a programmable data processor for performing theprocessing methods. Alternatively, the processing may be implemented inhardware, for example for processing an image data stream as it issupplied to the display device.

Another example of the use of a multiple view display is to provide adisplay which may be operated in a public viewing mode or in a privateviewing mode. In the public viewing mode, the display is required todisplay the same image or image sequence throughout a relatively wideviewing range, for example so that the display may be viewed by severalviewers simultaneously. However, when switched to the private mode, theviewing range for the intended viewer is made relatively narrow so thatthe image or image sequence being displayed cannot be viewed by anyoneelse. The multiple view displays described hereinbefore may be used forthis purpose.

In the public mode, the same image or image sequence is displayed by allof the pixels so as to provide the wide viewing range. The processingtechniques described hereinbefore are applied so as to improve the imagequality perceived by all of the viewers.

In the private mode, two or more different images are displayed. Theprivate image is displayed by one of the sets of pixels so as to beviewable in a relatively narrow viewing range, for example by anauthorised viewer. The other set or sets of pixels provide a differentimage display. For example, the other set or sets of pixels may displaya black image or an obscuring pattern which helps to hide the privateimage or image sequence so as to make it imperceptible to non-authorisedviewers. However, other images may be displayed such as pictures, textor images of a uniform colour or uniform brightness.

GB2428101 discloses a technique for producing a privacy effect in an LCDdisplay by imposing a degree of high frequency variation (a secondaryimage) on a source image (principal image). The secondary image is usedto modulate the vaccination imposed on the principal image to achievethe privacy effect. For example, the variation may be on a regular girdpattern similar to that produced by a parallax barrier in other types ofdisplay. The variation imposed on the image may create the same colourartefacts as found in other multiple-view displays, for example asdescribed hereinbefore. By processing the principle image using thetechniques described hereinbefore, the colour artefacts may besubstantially corrected.

1. A method of processing image data for display by a multiple-viewdisplay device, comprising: receiving a plurality of sets of image pixeldata, where each set represents the pixel brightness of a respectiveimage or sequence of images; and processing the sets of pixel data byapplying a unidirectional filter to each of at least one of the sets. 2.A method as claimed in claim 1, in which all of the sets are processedby respective unidirectional filters before interleaving.
 3. A method asclaimed in claim 2, in which the unidirectional filters are of the sametype.
 4. A method as claimed in claim 1, in which each set comprisescomposite colour component pixel group data and the or each filteroperates on adjacent composite pixel groups.
 5. A method as claimed inclaim 4, in which the or each filter operates on the pixel data of thesame colour components of the adjacent composite pixel groups.
 6. Amethod as claimed in claim 1, in which the or each filter forms eachprocessed pixel data as a linear combination of the unprocessed pixeldata and at least one adjacent pixel data.
 7. A method as claimed inclaim 6, in which the at least one adjacent pixel data is one adjacentpixel data.
 8. A method as claimed in claim 6, in which the linearcombination is a normalised linear combination.
 9. A method as claimedin claim 6, in which the at least one adjacent pixel data represents atleast one horizontally adjacent pixel.
 10. A method as claimed in claim1, in which the or each filter operates in real time.
 11. A method ofprocessing image data for display by a multiple-view display device,comprising: receiving a plurality of sets of image pixel data, whereeach set represents the pixel brightnesses of a respective image orsequence of images; processing the sets of pixel data by comparing, foreach of a plurality of subsets of each of at least one of the sets whereeach subset represents the brightnesses of a same number of pixel groupsand each pixel group comprises at least one pixel, the brightnesspattern of the pixel groups of the subset with a first predeterminedpattern; and, if the pixel brightness pattern substantially matches thefirst predetermined pattern, applying a first filter to derive a firstprocessed brightness of at least one of the pixel groups of the subset.12. A method as claimed in claim 11, in which the comparing stepcomprises forming the difference between the brightnesses of immediatelyadjacent pixel groups of each subset.
 13. A method as claimed in claim12, in which the comparing step further comprises comparing thedifferences with at least one threshold.
 14. A method as claimed inclaim 11, in which each pixel group comprises a composite colour pixelgroup of colour component pixels.
 15. A method as claimed in claim 14,in which the brightness of each pixel group is formed as a weighted sumof the brightnesses of the colour component pixels.
 16. A method asclaimed in claim 14, in which the brightness of each pixel group isformed as the brightness of one of the colour component pixels.
 17. Amethod as claimed in claim 16, in which the brightness of each pixelgroup is formed as the brightness of a green one of the colour componentpixels.
 18. A method as claimed in claim 11, in which, if the pixelbrightness pattern does not substantially match the first predeterminedpattern, a second filter is applied to derive a second processedbrightness of the at least one of the pixel groups.
 19. A method asclaimed in claim 18, in which the second filter is a unidirectionalfilter.
 20. A method as claimed in claim 11, in which, if the pixelbrightness pattern does not substantially match the first predeterminedpattern, no filter is applied for deriving the brightness of the atleast one of the pixel groups.
 21. A method as claimed in claim 11,comprising, for each of the plurality of subsets, comparing thebrightness pattern of the pixel groups of the subset with a secondpredetermined pattern and, if the pixel brightness pattern substantiallymatches the second predetermined pattern, applying a third filter toderive a third processed brightness of at least one of the pixel groupsof the subset.
 22. A method as claimed in claim 11, in which the pixelsof each subset are contiguous and extend substantially in one dimension.23. A method as claimed in claim 1, in which the pixels of each subsetcomprise a contiguous two dimensional arrangement.
 24. A method asclaimed in claim 11, in which the comparing step is repeated followingreceipt of each pixel group data.
 25. A method as claimed in claim 11,comprising interleaving the processed sets for supply to the displaydevice.
 26. A method of processing image data for display by amultiple-view display device, comprising: receiving a plurality of setsof image pixel data, where each set represents the pixel brightnesses ofa respective image or sequence of images; and processing the sets ofpixel data by applying, to each pixel of each of at least one of thesets, a correction to compensate for the absence of at least one omittedadjacent pixel of the same set.
 27. A method as claimed in claim 26, inwhich the at least one omitted adjacent pixel is omitted during asubsequent interleaving step.
 28. A method as claimed in claim 27,comprising performing the interleaving step on the processed sets forsupply to the display device.
 29. A method as claimed in claim 26, inwhich the at least one of the sets comprises all of the sets.
 30. Amethod as claimed in claim 26, in which the pixels represent grey levelsof monochrome images.
 31. A method as claimed in claim 26, in which thepixels represent brightnesses of colour components and at least oneomitted adjacent pixel is of the same colour component as the pixel. 32.A method as claimed in claim 26, in which the correction comprisesreplacing the pixel data with data representing a linear combination ofthe pixel data and at least one adjacent pixel data.
 33. A method asclaimed in claim 32, in which the linear combination comprises anormalised difference between: a normalised weighted sum of the pixeldata and a plurality of the adjacent pixel data; and a weighted sum ofthe adjacent pixel data omitting the omitted adjacent pixel data.
 34. Amethod as claimed in claim 33, in which the weights of the normalisedsum are substantially in accordance with at least one Gaussian function.35. A method as claimed in claim 34, in which the at least one functioncomprises a function which is rotationally symmetrical about the pixelbeing processed.
 36. A method as claimed in claim 34, in which the atleast one function comprises a first horizontal Gaussian function havinga first standard derivation and a second vertical Gaussian functionhaving a second standard deviation different from the first standarddeviation.
 37. A method as claimed in claim 36, in which the firststandard deviation is less than the second standard deviation.
 38. Amethod as claimed in claim 34, in which the weights are integerapproximations to the or each Gaussian function.
 39. A method as claimedin claim 26, in which the display device is arranged to display theimages or image sequences simultaneously.
 40. A method as claimed inclaim 26, in which the display device is an interleaved image displaydevice.
 41. A method as claimed in claim 26, in which the display devicecomprise an image display device and a parallax optic.
 42. A method asclaimed in claim 26, in which the sets comprise respective serial datastreams.
 43. An apparatus arranged to perform a method as claimed inclaim 26.